Advancements in artificial intelligence (“AI”) have expanded rapidly and for numerous applications. However, even in view of this rapid expansion, applications geared towards to the control of devices, particularly those that must respond to changes in circumstances, unknown variables, and/or ill-defined user preferences still face many hurdles. For example, in conventional systems, computer learning systems, such as artificial neural networks used for image analysis and other computer vision applications, may be trained based on a training data set. Through this training, the system may classify and make other determinations regarding images in data sets. For example, the artificial neural network may be trained to identify a particular object found in a plurality of images of a training data set. An image (e.g., from a test data set, as opposed to the training data set) may then be processed through the trained artificial neural network, and the trained artificial neural network may output a determination as to whether or not the image includes the object.